RESEARCH IN THE BIOCYBERNETICS LABORATORY these days is somewhat eclectic, but - as alway interdisciplinary. Our work typically involves integration of theory with real laboratory data, using biomodeling, computational and biosystems approaches. Our current problem domains are physiological systems, disease processes, pharmacology, and some post-genomic bioinformatics. The pedagogy of the lab involves development and exploitation of the synergistic and methodologic interface between structural and computational biomodeling with laboratory data, or computational systems biology, with a focus on integrated approaches for solving complex biosystem problems from sparse biodata (e.g. in physiology, medicine and pharmacology), as well as voluminous biodata (e.g. from genomic libraries and DNA array data).
Our primary neuroendocrine research involves thyroid hormone regulation and metabolism. Our long-term goal is to further enhance understanding of the hierarchical mechanisms of control of thyroid hormone (TH) production at the cellular level, organ distribution and metabolism and excretion of TH in mammals and fishes. Our approach is quantitative and integrative, with emphasis on both whole-organism and local organ/cellular TH regulation in health and disease states (integrated regulation of sources, sinks and action sites). Over the last 35 years, our contributions to the literature of TH metabolism and physiology have been realized using this integrated multidisciplinary investigative approach. In our earlier experimental work, physiology and biochemistry laboratory methodologies were supplemented with two distinct biomodeling and experiment design approaches pioneered in our laboratory. Both treat in vivo derived multiorgan-whole-body data, one collected from steady state tracer kinetic experiments using multisite hormone constant infusion inputs, the other from multisite hormone pulse-dose transient response kinetic experiments. The independent and complementary dynamic system data gleaned from these studies were quite useful for unraveling some of the quantitative aspects of TH regulation and cellular metabolism, as presented in our publications.
Our most recent TH regulation research is translational, using dynamic feedback control system simulation models, built and validated with human data. We are exploring causes and treatments for thyroid diseases, including thyroid cancer in adults and children, and congenital thyroid diseases in children. (See our recent publication in the journal Thyroid).
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The focus here is on kinetic modeling methodology development for specific applications in life science research. Emphasis is on dealing effectively with the particular limitations of biological data, model complexity and methods for designing kinetic experiments that optimize use of resources, including both laboratory and experimental animal resources. Current projects include:
Differential algebra approaches to:
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These activities complement our modeling methodology activities. They have provided some of the tools for performing our own experimental studies in neuroendocrinology. All are online (go to HOME page). Others are in progress.